Biblio

Found 13 results
Author Title Type [ Year(Asc)]
Filters: Author is Gienger, Michael  [Clear All Filters]
2011
Rolf M, Steil JJ, Gienger M.  2011.  Online Goal Babbling for rapid bootstrapping of inverse models in high dimensions. IEEE Int. Conf. Development and Learning and on Epigenetic Robotics (best student paper award). 2:1–8.
Gienger M, Muehlig M, Steil JJ.  2011.  Robot with automatic selection of task-specific representations for imitation learning. European Patent Office.
2010
Rolf M, Steil JJ, Gienger M.  2010.  Bootstrapping inverse Kinematics with Goal Babbling. :147–154.
Muehlig M, Gienger M, Steil JJ.  2010.  Human-Robot Interaction for Learning and Adaptation of Object Movements. IEEE Int. Conf. Intelligent Robots and Systems. :4901–4907.
Gienger M, Muehlig M, Steil JJ.  2010.  Imitating object movement skills with robots — A task-level approach exploiting generalization and invariance. The IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems : Conference Proceedings. :1262–1269.
Rolf M, Steil JJ, Gienger M.  2010.  Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
Neumann K, Rolf M, Steil JJ, Gienger M.  2010.  Learning Inverse Kinematics for Pose-Constraint Bi-Manual Movements. From Animals to Animats 11. 11th International Conference on Simulation of Adaptive Behavior, SAB 2010. Proceedings. 6226
Rolf M, Steil JJ, Gienger M.  2010.  Mastering Growth while Bootstrapping Sensorimotor Coordination. Int. Conf. on Epigenetic Robotics.
2009
Muehlig M, Gienger M, Steil JJ, Goerick C.  2009.  Automatic Selection of Task Spaces for Imitation Learning. IEEE International Conference on Intelligent Robots and Systems. :4996–5002.
Rolf M, Steil JJ, Gienger M.  2009.  Efficient exploration and learning of whole body kinematics. IEEE 8th International Conference on Development and Learning. :1–7.
Muehlig M, Gienger M, Hellbach S, Steil JJ, Goerick C.  2009.  Task-level Imitation Learning using Variance-based Movement Optimization. IEEE International Conference on Robotics and Automation. :1177–1184.